Graph Clustering

Graph Clustering is the process of grouping the nodes of the graph into clusters, taking into account the edge structure of the graph in such a way that there are several edges within each cluster and very few between clusters. Graph Clustering intends to partition the nodes in the graph into disjoint groups.

Source: Clustering for Graph Datasets via Gumbel Softmax

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 21–30 of 393 papers

Title	Date	Tasks	Status	Hype	Score
Adversarially Regularized Graph Autoencoder for Graph Embedding	Feb 13, 2018	ClusteringDecoder	CodeCode Available	1	5
Deep Temporal Graph Clustering	May 18, 2023	ClusteringDeep Clustering	CodeCode Available	1	5
Accurate Learning of Graph Representations with Graph Multiset Pooling	Feb 23, 2021	Graph ClassificationGraph Clustering	CodeCode Available	1	5
NCAGC: A Neighborhood Contrast Framework for Attributed Graph Clustering	Jun 16, 2022	ClusteringContrastive Learning	CodeCode Available	1	5
Attention-driven Graph Clustering Network	Aug 12, 2021	AttributeClustering	CodeCode Available	1	5
Efficient graph convolution for joint node representation learning and clustering	Feb 1, 2022	ClusteringGraph Clustering	CodeCode Available	1	5
Attributed Graph Clustering with Dual Redundancy Reduction	Apr 18, 2022	ClusteringContrastive Learning	CodeCode Available	1	5
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models	Jul 17, 2023	BenchmarkingGraph Clustering	CodeCode Available	1	5
Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance	Apr 20, 2020	ClusteringCommunity Detection	CodeCode Available	1	5
A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open Resource	Nov 23, 2022	AttributeClustering	CodeCode Available	1	5

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All datasets Citeseer Cora Pubmed Biase et al Bozec et al Deng et al Goolam et al Pollen et al Treutlein et al Yan et al

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	R-DGAE	ACC	70.5	—	Unverified
2	R-GMM-VGAE	ACC	68.9	—	Unverified
3	AGC	ACC	67	—	Unverified
4	RWR-GAE	ACC	61.6	—	Unverified
5	RWR-VGAE	ACC	61.3	—	Unverified
6	ARGE	ACC	57.3	—	Unverified
7	ARVGE	ACC	54.4	—	Unverified
8	GAE	ACC	40.8	—	Unverified
9	DAEGC+GSCAN†	NMI	39.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	R-GMM-VGAE	ACC	76.7	—	Unverified
2	R-DGAE	ACC	73.7	—	Unverified
3	AGC	ACC	68.92	—	Unverified
4	RWR-VGAE	ACC	68.5	—	Unverified
5	RWR-GAE	ACC	66.9	—	Unverified
6	ARGE	ACC	64	—	Unverified
7	ARVGE	ACC	63.8	—	Unverified
8	GAE	ACC	59.6	—	Unverified
9	DAEGC+GSCAN†	NMI	52.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	R-GMM-VGAE	ACC	74	—	Unverified
2	RWR-VGAE	ACC	73.6	—	Unverified
3	RWR-GAE	ACC	72.6	—	Unverified
4	R-DGAE	ACC	71.4	—	Unverified
5	AGC	ACC	69.78	—	Unverified
6	VGAE	ACC	65.48	—	Unverified
7	DAEGC+GSCAN†	NMI	31.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.81	—	Unverified